SummaryThe Automated Telephone Diabetes Management program, a part of the Improving Diabetes Efforts Across Language and Literacy (IDEALL) project at the Community Health Network of San Francisco, provided automated telephone monitoring of individuals with poorly controlled type II diabetes who receive their care at four safety net clinics in San Francisco. An adjunct to regular clinic care, the system made weekly automated, interactive calls to participants in their native language (English, Spanish, or Cantonese), with followup calls made as needed by a nurse care manager with appropriate language skills. The intervention enhanced patients' engagement in the self-management of their condition, improved health behaviors and outcomes, and increased detection of adverse and potentially adverse situations.Strong: Evidence consists of data from a three-arm randomized controlled trial that showed improvements on key measures. Efforts were made to include diverse patients and clinics.
Developing OrganizationsCommunity Health Network of San Francisco; San Francisco Department of Public Health; University of California, San Francisco Center for Vulnerable Populations
Use By Other Organizations
- The Community Health Network of San Francisco is currently working with the San Francisco Health Plan to implement this program for all enrollees with diabetes, including individuals covered by Medicaid. This implementation will use non-nurse personnel, such as health coaches, to provide the main response to automated telephone diabetes management calls, with backup provided by nurses. It will also test a medication intensification component, linking the patient-reported data gathered from automated telephone calls with additional pharmacy claims information (e.g., whether a patient picked up his insulin as scheduled).
- Other organizations that have adopted the IDEALL automated telephone diabetes management model include Southern California Kaiser Permanente Medical Group, who are using automated telephone technology to pursue a Treat to Target home medication intensification intervention, and the University of California, San Francisco Oral Health Disparities Program, who are developing an automated telephone messaging intervention to administer multilingual health promotion messages about oral health for children.
Date First Implemented2003
Vulnerable Populations > Non-english speaking/limited english proficiency
Problem AddressedLow health literacy and/or limited proficiency in English is common among patients with diabetes, and these factors affect patients' abilities to understand and manage the disease effectively. Inadequate physician communication can create further barriers to care for these patients.
- Less knowledge, worse disease management: Low health literacy is common among patients with diabetes and has been found to be linked with poor knowledge of the disease and its complications; worse glycemic control; and higher rates of retinopathy, a complication of diabetes that can result in blindness.1-3
- Lack of communication creates greater barriers to care: Physicians often overestimate the health literacy of their patients with diabetes, failing to assess patients' recall and comprehension of new concepts during visits. This highly variable and often inadequate provider-patient communication can make it difficult for patients to access the information and support they need to manage their disease.4
- Tailored disease management systems can improve care: Previous studies conducted at the Community Health Network of San Francisco indicate that physicians believe that tailored disease management systems can improve diabetes care for their patients with limited health literacy.4
Description of the Innovative ActivityThe Automated Telephone Diabetes Management program provided telephone-based, interactive monitoring of participants’ diabetes management strategies in their native language with telephone followup by language-concordant nurse case managers when appropriate. The components of the program included the following:
- Program enrollment and orientation: Researchers created a registry of eligible patients from clinic files at the Community Health Network of San Francisco. Using this registry, researchers recruited clinics to participate in the clinical trial based on the number of eligible patients identified at each site. Eligible patients had a diagnosis of adult type 2 diabetes; had one or more primary care visits in the previous 12 months; spoke English, Spanish, or Cantonese; did not have limited vision or were not hearing-impaired; and had no diagnoses of psychotic illness or end-stage renal disease. The project enrolled patients at participating clinics through provider referral or by approaching them during their routine visits to the clinic. Recruited patients attended a baseline session in which they completed informed-consent forms and a questionnaire about preferred day and time for call, had their literacy assessed, and had a physiologic measurement conducted. Similar programs have been created for patients with gestational diabetes mellitus and Chronic Kidney Disease.
- Weekly automated calls: Each week, participants received a 6- to 12-minute automated call in their native language (English, Spanish, or Cantonese). The system asked the patient to respond to rotating questions regarding self-care, psychosocial issues, and referrals for preventive services (e.g., number of days in last 7 in which blood sugar was tested, number of days in last 7 in which they consumed fresh fruits and vegetables, number of days in the last 7 in which they missed even one insulin shot) and also provided tailored health messages. The program used interactive response technology with touchtone (not voice) response. Patients selected the time they would like to be called at enrollment; however, they could change their preferred time or call the system toll-free instead of receiving the call at the appointed time.
- Nurse callback for select patients: Participants answering “out of range” on selected queries, based on predetermined clinical thresholds (e.g., those responding that they had taken all their insulin shots on 0 to 4 days within the last 7 or that they had consumed fresh fruits and vegetables on 0 to 3 days within the last 7), received a callback from their nurse care manager within 24 to 72 hours. The nurse, who spoke the patient’s native language, worked with the patient to develop an “action plan” for solving the issue identified during the call (e.g., setting a weekly goal for glucose monitoring, medication adherence, or exercise).
- Documentation: Project staff documented all care manager–patient interactions with a standardized record linked to the Community Health Network of San Francisco patient health record. A patient’s physician could access this record.
Context of the InnovationThe Automated Telephone Diabetes Management program was a component of the IDEALL project, a practical clinical trial designed by the University of California, San Francisco Center for Vulnerable Populations to test and compare methods for improving diabetes outcomes among primary care patients in the safety net system in San Francisco, CA. IDEALL was implemented as part of an overall effort by the San Francisco Department of Public Health Community Health Network to improve the quality of chronic disease care in its primary care clinics.4 The project compared two interventions, the Automated Telephone Diabetes Management program and a group medical visit, to usual care. These interventions were selected for a number of reasons, including prior evidence of their effectiveness, their ability to overcome language and literacy barriers, their focus on system change rather than physician behavior change, their use of a multidisciplinary team, their relative low cost, and project staff's belief that each of these interventions would be welcomed by clinicians and administrators at the Community Health Network of San Francisco.4
ResultsResults from a randomized clinical trial (RCT) comparing 112 intervention participants with patients receiving either group medical visits (n = 113) or routine care (n = 114) suggest that the Automated Telephone Diabetes Management intervention generated significant engagement in care and clinical activity for patients, improved health behaviors and outcomes, and enhanced detection of adverse events.
Strong: Evidence consists of data from a three-arm randomized controlled trial that showed improvements on key measures. Efforts were made to include diverse patients and clinics.
- Enhanced patient engagement: Patients participating in the intervention for a period of 9 months reported more engagement in their care (e.g., participation in calls, participation in nurse callbacks, and generation of action plans in response to callbacks) than did a comparison group of patients who received either a group medical visit intervention or the usual care. Of the patients participating in the intervention, 93.8 percent responded to one or more automated calls, as compared to 69.6 percent of the patients in the comparison medical visit intervention group who attended one or more group medical visits. These findings were particularly strong for those with limited English proficiency and those with limited literacy in both English and Spanish.5
- Improved self-management behavior and health outcomes: One year post-intervention, participants who received automated calls reported significant increases in self-management behavior, including improved foot care and increased physical activity, over those patients who received group medical visits or usual care. In addition, automated call participants reported significant decreases in days restricted to bed and were less likely to report that diabetes prevented them from carrying out daily activities.6
- Detection of potential problems: The system enhanced the clinic’s ability to identify adverse (e.g., an injury) and potentially adverse (an unsafe state likely to lead to injury if it persists without intervention) situations. Among the patients participating in the intervention, 11 percent of all automated calls identified an adverse or potentially adverse situation, with a total of 111 adverse and 153 potentially adverse situations detected.7 This detection allowed for quick intervention to minimize harm to the patient.
Planning and Development ProcessKey steps in the planning and development process include the following:
- Review of earlier studies: Project leaders developed the IDEALL Project and the Automated Telephone Diabetes Management component after a review of four earlier Community Health Network studies found that limited health literacy and English proficiency were common, significant barriers to quality care for chronic disease. These studies also indicated that physicians believed that patients with limited health literacy could benefit from tailored diabetes management systems.4
- Decision to make the program an adjunct: The Community Health Network implemented IDEALL as an adjunct to care provided in the primary care clinics because the investigators did not believe the clinics would be able to sustain the interventions, including the planning, training, recruitment, and ongoing project management required. Project staff hoped that with favorable results, the intervention might be integrated into routine clinical care.
- Training: Nurse care managers received 2 hours of formal training in motivational interviewing and interpretation of computerized Automated Telephone Diabetes Management results.
- Developing telephone scripts: Researchers at the University's Center for Vulnerable Populations spent close to 1 year developing the program's automated telephone scripts, conducting extensive piloting, and eliciting feedback from Community Health Network patients.
Resources Used and Skills Needed
- Staffing: Staffing for the pilot project included a project leader, two nurse care managers, and 1.5 to 2 full-time equivalent research associates to do the following: prepare, record, and translate messages; set up and maintain the system (an outside vendor can do this as well); and recruit and orient patients.
- Costs: The total costs during the trial were $782 per patient; the trial included 112 patients who were provided the service over a 9-month period. This figure includes startup costs (e.g., staff time or vendor fees for setting up the automated telephone diabetes management system, developing and translating messages and protocols, and training nurse care managers) and ongoing implementation costs (e.g., nurse care manager time, staff time to recruit and retain participants, telephone expenses, and monthly service fees). Many of the costs associated with the program are fixed in nature, which makes the per-patient costs artificially high due to the small number of participants.
Funding SourcesAgency for Healthcare Research and Quality; National Institutes of Health; The Commonwealth Fund; California Healthcare Foundation; San Francisco Department of Public Health
Tools and Other ResourcesHealthcare 411: News Series From AHRQ. Podcast: Addressing Low Health Literacy at the Community Level. December 12, 2012. Available at: http://healthcare411.ahrq.gov/radiocastseg.aspx?id=1338&type=seg
McLean I, Schneiderman M, Palacios J, et al. Automated Telephone Disease Management (ATDM) Protocol, 2004. Available at: http://www.commonwealthfund.org/usr_doc/ATDM_protocol_102404.pdf?section=4057 (If you don't have the software to open this PDF, download free Adobe Acrobat Reader® software .).
McLean I, Hammer H, Lin L, et al. Group Visit Facilitators Training Manual and Protocol. Available at: http://www.commonwealthfund.org/usr_doc/CWF_TrainingGuide-Protocol_4-28-06.pdf?section=4057.
Getting Started with This Innovation
- Obtain buy-in from management: Executive-level buy-in is essential to support the cost and effort involved in such a project.
- Establish a clinical champion: Appoint a trusted team member to champion the project, motivating staff participation and promoting accountability.
- Ensure adequate technology: Make sure the project site has the technological capacity to support the intervention, including interactive voice response or automated calling.
- Train and support nurse response team: As the primary contact with patients in this intervention is through nurse care managers, ensure that all nurses delivering and responding to patient calls are appropriately trained and provided with ongoing support and education.
Sustaining This Innovation
Explore cost-cutting measures: Seek ways to reduce per-patient costs. For example, multiple clinics could collaborate on the project or could implement it in conjunction with a health plan. In addition, properly trained medical assistants (who are less expensive than nurse managers) could potentially make callbacks to patients.
Add program components for wider impact: Consider linking this program to a strategy designed to increase medication intensification, which has greater potential for a positive impact on metabolic measures (e.g., blood glucose and lipid levels).
- Appropriate technology can disproportionately engage vulnerable populations.
- More robust clinical improvements would require linking the intervention to medication intensification.
Contact the InnovatorDean Schillinger, MD
Professor of Medicine in Residence
Director, University of California, San Francisco Center for Vulnerable Populations
Bldg 10, 3rd floor San Francisco General Hospital
1001 Potrero Avenue
San Francisco CA 94110
Phone: (415) 206-8940
Fax: (415) 206-5586
Margaret A. Handley, PhD MPH
Associate Professor in Epidemiology and Biostatistics and Medicine
University of California, San Francisco Center for Vulnerable Populations
Bldg 10, 3rd floor San Francisco General Hospital
1001 Potrero Avenue
San Francisco CA 94110
References/Related ArticlesBetter Diabetes Care for Patients With Low Health Literacy. The Commonwealth Fund, 2004. Available at: http://www.commonwealthfund.org/Content/Innovations/Tools/2004/Jun/Better-Diabetes-Care-for-Patients-with-Low-Health-Literacy.aspx.
Handley MA, Hammer H, Schillinger D. Navigating the terrain between research and practice: a Collaborative Research Network (CRN) case study in diabetes research. J Am Board Fam Med. 2006;19(1):85-92. [PubMed]
Handley MA, Schillinger D, Shiboski S. Quasi-experimental designs in practice-based research settings: design and implementation considerations. J Am Board Fam Med. Sep-Oct 2011;24(5):589-596. [PubMed]
Handley MA, Shumway M, Schillinger D. Cost-effectiveness of automated telephone self-management support with nurse care management among patients with diabetes. Ann Fam Med. 2008 Nov/Dec;6(6):512-8. [PubMed]
Kim Y, Situ M, Handley M, et al. Ecology matters: contextualizing safety-net patients' experiences with diabetes self-management support strategies. Asia-Pacific Journal of General Practice. 2009 Oct;1(1):1-14.
Ratanawongsa N, Bhandari VK, Handley M, et al. Primary care provider perceptions of the effectiveness of two self-management support programs for vulnerable patients with diabetes. J Diabetes Sci Technol. 2012;6(1):116-124. [PubMed]
Ratanawongsa N, Handley MA, Quan J, et al. Quasi-experimental trial of diabetes Self-Management Automated and Real-Time Telephonic Support (SMARTSteps) in a Medicaid managed care plan: study protocol. BMC Health Services Research, 2012. [PubMed]
Schillinger D, Piette J, Grumbach K, et al. Closing the loop: physician communication with diabetic patients who have low health literacy. Arch Intern Med. 2003 Jul;163(1):83-90. [PubMed]
Schillinger D, Bindman A, Wang F, et al. Functional health literacy and the quality of physician-patient communication among diabetes patients. Patient Educ Couns. 2004 Mar;52(3):315-23. [PubMed]
Seligman HK, Wang F, Palacios JL, et al. Physician notification of their diabetes patients’ limited health literacy. A randomized, controlled trial. J Gen Intern Med. 2005 Nov;20(11):1001-7. [PubMed]
Schillinger D, Hammer H, Wang F, et al. Seeing in 3-D: examining the reach of diabetes self-management support strategies in a public health care system. Health Educ Behav. 2008 Oct;35(5):664-82. [PubMed]
Schillinger D, Handley M, Wang F, et al. Effects of self-management support on structure, process, and outcomes among vulnerable patients with diabetes: a three-arm practical clinical trial. Diabetes Care. Apr 2009;32(4):559-566. [PubMed]
Sarkar U, Handley M, Gupta R, et al. Use of an interactive, telephone-based self-management support program to identify adverse events among ambulatory diabetes patients. Journal of General Internal Medicine. 2008;23(4):459-465. [PubMed]
DeWalt DA, Berkman ND, Sheridan S, et al. Literacy and health outcomes: a systematic review of the literature. J Gen Intern Med. 2004 December;19(12):1228-39. [PubMed]
Schillinger D, Grumbach K, Piette J, et al. Association of health literacy with diabetes outcomes. JAMA. 2002 Jul 24-31;288(4):475-82. [PubMed]
Handley MA, Hammer H, Shillinger D. Navigating the terrain between research and practice: a Collaborative Research Network (CRN) case study in diabetes research. J Am Board Fam Med. 2006 Jan-Feb;19(1):85-92. [PubMed]
Schillinger D, Hammer H, Wang FW, et al. Seeing in 3-D: examining the reach of diabetes self-management support strategies in a public health care system. Health Educ Behav. 2008 Oct;35(5):664-82. [PubMed]
Schillinger D, Handley M, Wang F, et al. Effects of self-management support on structure, process, and outcomes among vulnerable patients with diabetes. Diabetes Care. 2009 April;32(4). [PubMed]
Sarker U, Handley M, Gupta R, et al. Use of an interactive, telephone-based self-management support program to identify adverse events among ambulatory diabetes patients. J Gen Intern Med. 2008 April;23(4):459-65. [PubMed]
Lyles CR, Schillinger D, Lopez A, et al. Safety events during an Automated Telephone Self-Management Support Intervention. J Diabetes Sci Technol. 2013 May 1;7(3):596-601. [PubMed]
Quasi-experimental trial of diabetes Self-Management Automated and Real-Time Telephonic Support (SMARTSteps) in a Medicaid managed care plan: study protocol. BMC Health Serv Res. 2012 Jan 26;12:22. [PubMed]
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Original publication: August 29, 2008.
Original publication indicates the date the profile was first posted to the Innovations Exchange.
Last updated: September 25, 2013.
Last updated indicates the date the most recent changes to the profile were posted to the Innovations Exchange.
Date verified by innovator: May 21, 2012.
Date verified by innovator indicates the most recent date the innovator provided feedback during the annual review process. The innovator is invited to review, update, and verify the profile annually.